The present invention relates to a method enabling multiple-antenna equalization in a radioelectrical receiver, enabling the reception of a digital radioelectrical signal of the series linear modulation type (or the like) on at least two antennas in the presence of several propagation paths, also called multiple paths, or in the presence of interfering sources also called jammers.
The invention also relates to a multiple-antenna radioelectrical receiver using such a method.
It can be applied especially to the implementation of HF transmission systems and of the base stations of GSM mobile radio communications systems.
In these systems, the transmitted signal comes from the phase and/or amplitude modulation of a carrier on a sequence of symbols of which a portion, known to the receiver, are called "learning sequences".
The channel may be that of transmissions in the high frequency (HF) range enabling long-distance communications (at distances of hundreds to thousands of kilometers). The multiple paths of the HF channel are due to the multiple reflections of the signal on the ionospheric layers of the atmosphere and on the ground. The channel may also be that of transmissions in the UHF or ultra-high frequency range used in mobile radio communications (for example GSM communications). The multiple paths of the mobile radio channel are due to multiple reflections on the surfaces of buildings and on terrestrial surface features.
As for jamming, it may be deliberate (wideband jamming for example) or involuntary (by other transmission signals using the same frequency band).
In many systems presently in operation, the matching with the characteristics of the transmission channel is made possible by the insertion, in the waveform, of learning sequences known to the receiver. There are then various possible ways to obtain the adaptive equalization of the useful signal received. Several approaches are described for example in the article by J. J. Proakis entitled "Adaptive equalization for TDMA digital mobile radio", IEEE Trans. on Vehicular Technology, Vol. 40, No. 2, May 1991. The processing referred to is a form of equalization based on the Viterbi algorithm associated with an estimation of the transmission channel by means of learning sequences. This approach is commonly used in GSM systems.
In the context of HF transmissions at high bit rates (2400 bauds), less complex approaches are preferred. These less complex approaches are provided by a simplified version of the Viterbi algorithm, the M-algorithm described in particular in an article by A. Baier and G. Heinrich entitled "Performance Of M-algorithm MLSE Equalizers In Frequency-Selective Fading Mobile Radio Channels", Proc. of 1989 International Conference on Communications, ICC'89, or again by a decision feedback equalizer or FE. This may be obtained by means of self-adaptive filters adapted by a recursive least-error squares type algorithm in preference to a gradient algorithm for reasons of speed of convergence, or it may be computed from an estimation of the transmission channel as in the article by P. K. Shukla and L. F. Turner, "Channel-Estimation-Based Adaptive DFE For Fading Multipath Radio Channels", IEEE Proceedings-I, Vol. 138, No. 6, December 1991.
When there is "fading", the variation of the power of the signals received leads to a deterioration of the performance characteristics in terms of the binary error rate (BET). The use of several antennas in equalizers with a diversity of antennas enables compensation for deterioration by taking advantage of the difference between the transmission channels corresponding to the different antennas.
In the presence of jamming, these equalization techniques become soon inefficient and specific anti-jamming techniques are necessary. These are, for example, error correction encoding, the excision of jamming by notch filtering, or the use of frequency hopping links. These techniques are used in many operational systems but are nevertheless limited when the interference phenomena are strong and occupy the entire band of the useful signal. It thus becomes appropriate to use anti-jamming means of greater efficiency, based on the use of antenna filtering techniques.
Antenna filtering techniques appeared in the early '60s. A summary description of these techniques is given in the doctoral thesis by P. Chevalier, "Antenne adaptative: d'une structure lineaire a une structure non lineaire de Volterra" ("Adaptive antennas: from a linear structure to a non-linear Volterra structure"), Universite de Paris Sud, June 1991. These techniques are designed to combine the signals received by the different sensors constituting the antenna so as to optimize its response to the scenario involving useful signals and jammers.
Since the conditions of propagation and jamming may change in the course of time, it is necessary to be able to adapt the antenna in real time to these variations by the use of a special antenna filtering technique known as the "adaptive antenna" technique. An adaptive antenna is an antenna that detects interference sources automatically by constructing holes in its radiation pattern in the direction of these interferences while at the same time improving the reception from the useful source, without any prior knowledge about the interferences and using minimum information on the useful signal Furthermore, through the tracking capacity of the algorithms used, an adaptive antenna is capable of automatic response to a changing environment.
Until very recently, it was always envisaged, in transmission systems, to have operation independent of the single sensor and adaptive antenna based techniques of adaptive equalization. This leads to sub-optimal performance characteristics. Thus, the system described by R. Dobson in "Adaptive Antenna Array", patent No. PCT/AU85/00157, February 1986, which discriminates between useful signals and jammers by time, manages to reject interferences efficiently but does not seek to optimize the useful signal/noise ratio.
In a context of transmission, and when learning sequences are introduced into the waveform, it is preferable to use techniques of antenna processing with discrimination by modulation as they optimize the useful signal/noise ratio thus preventing the implementation of a goniometric step. However, most of the techniques employed today use complex weights on each of the sensors of the adaptive antenna. An antenna of this kind enables the rejection of the interferences, but in the presence of multiple paths of propagation:
it "aims" in the direction of one of the paths, i.e. it rephases the contributions of this path with the different sensors (for omnidirectional sensors, therefore, a gain in signal-to-noise ratio of 10 log N is obtained, where N is the number of sensors used), PA1 and seeks to reject the paths decorrelated from this one, thus losing the energy associated with these paths. PA1 an article by P. Balaban and J. Salz entitled "Optimum Diversity Combining and Equalization in Digital Data Transmission with Applications to Cellular Mobile Radio--Part I: Theoretical Considerations", IEEE Trans. on Com., Vol. 40, No. 5, pp. 885-894, May 1992, PA1 a patent by G. P. Labedz et al. (Motorola Inc., Schaumburg, Ill., USA) entitled "Method and Apparatus for Diversity Reception of Time-Dispersed Signals", patent No. EP 430481.A2, 12.12.1991, PA1 a patent by Okanoue and Kazuhiro (NEC Corp., Tokyo, Japan) entitled "Noise-Immune Space Diversity Receiver", patent No. EP 449327.A2, Mar. 29, 1991, and PA1 an article by P. Jung, M. Na.beta.han and Y. Ma entitled "Comparison of Optimum Detectors for Coherent Receiver Antenna Diversity in GSM Type Mobile Radio Systems", Proc. of the 4th International Symposium on Personal, Indoor and Mobile Radio Communications, PIRMC'93, Yokohama, Japan, 1993. PA1 estimating the transmission channel on each of the antennas, PA1 estimating the background noise component plus interference on each of the antennas on the basis of the estimation of the transmission channel, PA1 estimating the spatial correlation matrix, referenced R.sub.b, of the background noise component plus interferences from the received signal, PA1 computing a spatial-temporal filter formed for each discrete temporal element of the estimated multiple-sensor channel of a spatial filter, PA1 achieving a temporal filtering of the data elements on the different sensors by the spatial-temporal filter, and PA1 equalizing the signal at output of the spatial-temporal filter by one-dimensional equalization at a symbol rate deciding the symbols transmitted.
In order to improve the performance characteristics of the last-named antenna processing technique, the idea is to couple it to a monosensor equalization technique. Multiple-antenna equalizers are thus obtained comprising a spatial part consisting of different filters positioned on each of the reception antennas and a temporal part positioned at output of the spatial part.
Receivers that carry out the joint processing of signals coming from several antennas have already been proposed to combat the selecting "fading" generated by the multiple paths in an unjammed environment. These are spatial diversity equalizers. As in monosensor equalization, the most commonly used solutions comprise either a Viterbi algorithm or a DFE structure minimizing the root mean square error (RMS error) between an obtained output and a desired output.
Spatial diversity equalizers based on a Viterbi algorithm are proposed especially in:
Their implementation requires prior knowledge of the pulse response of the transmission channel. When there is no jamming, the pulse response of the channel is estimated on the basis of the known symbols and the symbols decided as and when needed by the equalizer.
DFE structure spatial diversity equalizers are proposed in the article by P. Balaban and J. Salz and in an article by K. E. Scott and S. T. Nichols entitled "Antenna Diversity with Multichannel Adaptive Equalization in Digital Radio", Proc. of International Conf. on Com., ICC'91, New York, N.Y., USA, June 1991.
The last-named equalizer is made with self-adaptive filters whose coefficients are adapted by a least error squares algorithm. For the equalizer presented by P. Balaban and J. Salz, the coefficients are computed on the basis of an estimation of the transmission channel. The problem of the jammed environment is no longer dealt with in the study of these equalizers.
The spatial diversity equalizers referred to have been designed to combat the selective "fading" engendered by the multiple paths of the transmission channel, but not at all to reject interferences. However, of these equalizers, only the self-adaptive spatial diversity equalizer proposed by K. Scott and S. Nichols has the capacity to fulfil this last-named function. There is then obtained the transversal and recursive antenna which was the object of a doctoral thesis by L. Fety entitled "Methodes de traitement d'antenne adaptees aux radiocommunications" (Antenna Processing Methods Adapted to Radiocommunications), at the ENST, June 1988.
However, this processing can be applied only to transmission channels for which the time dispersal of the multiple paths in relation to the symbol duration is reduced, which is generally not the case in HF transmissions at high bit rates and in the GSM system. Indeed, in this context, the number of coefficients to be adapted is far too great for the adaptation algorithm to be capable of converging on a known learning sequence. The other spatial diversity equalizers presented depend on the estimation of the transmission channel which can hardly be obtained in the presence of interference. Furthermore, these equalizers do not integrate the interference rejection function.
In order to overcome the above-mentioned drawbacks, the present Applicant has filed a French patent published under No. 2 716 761 entitled "Procede permettant une egalisation multivoie dans un recepteur radioelectrique, en presence d'interferences et de multitrajets de propagation" (Method enabling a multiple antenna equalization in a radioelectrical receiver in the presence of interferences and multiple paths of propagation). This method provides jointly for a multiple-sensor equalization processing of the useful signal and a jammer rejection processing. It has the advantage of being an optimal method in the presence of temporally white noise (background noise+jammers), whatever the nature of the useful propagation channel. However, it leads to computation power that may have to be reduced in certain applications.
To this end, a French patent application entitled "Procede d'egalisation multicapteur permettant une reception multicapteur en presence d'interferences et de multitrajets de propagation, et recepteur pour sa mise en oeuvre" (Multiple-sensor equalization method enabling multiple-sensor reception in the presence of interferences and multiple paths of propagation, and receiver for its implementation) under number 95 14914, was filed on Dec. 15, 1995 by the present Applicant. It relates to a multiple sensor equalizer possessing computation power that is lower than the computation power of the multiple sensor receiver described in the above-mentioned patent application but can lead to lower efficiency performance when the useful propagation channel comprises several paths, owing to the fact that the multiple-sensor receiver is not the optimum in the presence of temporally white noise.